Presenter
Carolyn Talmadge joined the Research Technology team at Tufts University in 2013 after graduating from Tufts School of Engineering with an M.S in Environmental Health. Carolyn currently works as the Senior GIS Specialist and teaches the GIS for Conservation Medicine course within the Cummings School of Veterinary Medicine. Carolyn manages the Data Labs and participates in GIS projects, classes and grants across all schools and departments. Carolyn’s research interests focus on the One Health paradigm and using geospatial tools to investigate the spatial relationships between environmental health, animal health and public health issues facing us in today’s world.
Description
Wouldn’t it be great if ArcGIS was less expensive, easier to use, and more versatile? Never fear, QGIS is here! QGIS is a free and open-source Geographic Information System (GIS) software that allows you to create, edit, visualize, analyze and publish geospatial data on Windows, Mac, and Linux platforms.
This workshop will introduce users to introductory GIS concepts using QGIS. We will cover:
- What is GIS and who is using it?
- What are the different GIS softwares and why is QGIS a great option?
We will also do a hands-on activity in QGIS that involves exploring who has access to healthy foods in Cambridge, Massachusetts. This activity will teach users how to:
- Add GIS data to QGIS – including shapefiles and excel data using Lat/Longs
- How to symbologize (stylize) the data appropriately
- How to use tools such as Select by Attributes, Select by Location and Buffers
- How to create a final map composition including all necessary map elements.
Presenters
Elena Naumova, Tufts Friedman School of Nutrition Science and Policy
Mingfei Li, Bentley University
Kevin Mentzer, Bryant University
Description
This session will provide an open forum for professors, researchers, and students to discuss techniques for teaching data analytics. We hope to identify ways to teach graduate students to solve complex problems, think critically, and effectively communicate across inter-generational, trans-disciplinary research terms. We will discuss a data-intensive, project-based learning approach that emphasize collaborative learning to design, evaluate, and disseminate research in team environments. In particular, we will discuss ways for students to serve as both leads and reviewers of their own and their peers’ works.
Presenter
Kyle Monahan, Tufts University
Description
This aim of this workshop is to teach students how to run, view, and extract various summary statistics in R software, focusing on some of the unique capabilities of this software package. Topics include importing external data (R/Excel/XPT/DTA files), generating summary tables, graphical exploratory data analysis, correlations, performing simple linear and log-linear regressions, regression diagnostics, and extracting statistics for use in scientific paper writing. This workshop will demonstrate a data workflow process and the packages used for completing statistical analyses in data science research. The workshop will provide hands-on experience using practice datasets. This practical session will primarily use R, though strengths and limitations will be discussed across other statistical packages. Learning resources for each statistical package will also be discussed so participants can expand their skills outside of the workshop.
Presenter
Laurie LaRusso, MS, ELS, has been writing about health and medicine for a variety of audiences and in a variety of formats for more than 20 years. Her publications and presentations run the gamut from clinical research and continuing medical education to consumer health and patient education. Her focus is crafting text and graphics to tell data stories. She is a past-president of the American Medical Writers Association—New England Chapter and a winner of the chapter’s Will Solimene Award for Excellence in Medical Communication. She holds a Master’s degree in Health Communication from the Tufts University Graduate Programs in Public Health; certification as an Editor, Life Sciences from the Board of Editors in the Life Sciences; and an adjunct faculty appointment in the Nutrition Interventions, Communication, and Behavior Change program at Tufts University Friedman School of Nutrition Science and Policy.
Description
This workshop offers best practices for communicating data sciences and analytics results to various audiences. Topics include: considering your intended audience; choosing the best format for the selected audience; extracting and highlighting the essential information to tell your data story; and utilizing visual communication to engage your audience. Participants will learn how to break down and disseminate important data and results for science and nonscience audiences.
Presenter
Ken Chui, Tufts School of Medicine
Description
Starting an analysis with a clear motive can enhance our efficiency and avoid modeling pitfalls. The aim of this workshop is to provide a survey of different modeling motives, including explanatory, descriptive, and predictive models, and how our chosen motive would affect our procedure. We will facilitate the understanding by demonstrating the different procedures on the same data set. After the workshop, attendees will be able to better identify the core motive of an analysis and comment on the use of modeling procedure. Pre-requisite: basic knowledge in hypothesis testing and linear regression.
Presenter
Tania Alarcon Falconi, Environmental Health and Engineering
Description
This workshop aims to demonstrate techniques for effective data visualization using clear, detailed graphics. Topics covered include data visualization selection; when and when not to use graphics; proper fitting of data results to chart types; and stylistic choices to highlight important information. Participants will learn how to create and critique data visualizations.
Presenters
Ye Shen, Tufts Food Aid Quality Review
Ilana Cliffer, Tufts Food Aid Quality Review
Devika Suri, Tufts Food Aid Quality Review
Breanne Langlois, Tufts Food Aid Quality Review
Description
This workshop discusses the process of data management and analysis through the experience of the Food Aid Quality Review project, which conducted 3 large-scale field trials in Malawi, Burkina Faso, and Sierra Leone. Challenges, strengths, and lessons learned will be discussed. The session aims to provide participants with an understanding of how to work effectively as a team to conduct data management and analysis in complex field settings
Presenter
Sam Scarpino, Network Science Institute, Northeastern University
Description
This workshop aims to introduce complex systems and network analyses for application in nutrition science research. This includes tracking infectious disease outbreaks, analyzing spatial correlations of famine in complex emergencies, and modeling food systems. Network modeling will be presented conceptually and supported using examples of research from a broad audience.
